Cloud-computing facilities provide computational bandwidth and data-storage services much as utility companies provide electrical power and water to consumers. Cloud computing provides enormous advantages to customers without the devices to purchase, manage, and maintain in-house data centers. Such customers can dynamically add and delete virtual computer systems from their virtual data centers within public clouds in order to track computational-bandwidth and data-storage needs, rather than purchasing sufficient computer systems within a physical data center to handle peak computational-bandwidth and data-storage demands. Moreover, customers can completely avoid the overhead of maintaining and managing physical computer systems, including hiring and periodically retraining information-technology specialists and continuously paying for operating-system and database-management-system upgrades. Furthermore, cloud-computing interfaces allow for easy and straightforward configuration of virtual computing facilities, flexibility in the types of applications and operating systems that can be configured, and other functionalities that are useful even for owners and administrators of private cloud-computing facilities used by a customer.
Many data centers use a rata center management product with capacity and project planning tools that provide recommendations based on what-if scenarios. The recommendations provide data center customers with what can be reclaimed and what may or may not fit into the current environment of the physical data center infrastructure. Data center customers may ask questions and receive predictions based on adding or removing hardware capacity and/or by increasing or decreasing workloads in terms of hardware resource utilization. However, data center customers typically want to plan data center capacity requirements in order to meet potential changes in demand for access to their application programs. However, data center management products do not provide such planning capabilities and do not calculate a relationship between changes in usage of the application program and capacity of data center resources. As a result, data center customers have to try and estimate capacity changes due to changes in application program usage based on historical business metric data. For example, a data center customer typically tries to predict potential changes in CPU and memory utilization in the event of an increased number of users of the customer's application program based on historical usage data.